| Annals of Information Systems U Apte, U Karmarkar, U Kulkarni, DJ Power, R Sharda, S Kozielski, ... | 439 | 2009 |
| Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction SF Crone, M Hibon, K Nikolopoulos International Journal of forecasting 27 (3), 635-660, 2011 | 388 | 2011 |
| Forecasting and operational research: a review R Fildes, K Nikolopoulos, SF Crone, AA Syntetos Journal of the Operational Research Society 59 (9), 1150-1172, 2008 | 380 | 2008 |
| Neural network ensemble operators for time series forecasting N Kourentzes, DK Barrow, SF Crone Expert Systems with Applications 41 (9), 4235-4244, 2014 | 371 | 2014 |
| The impact of preprocessing on data mining: An evaluation of classifier sensitivity in direct marketing SF Crone, S Lessmann, R Stahlbock European Journal of Operational Research 173 (3), 781-800, 2006 | 321 | 2006 |
| Instance sampling in credit scoring: An empirical study of sample size and balancing SF Crone, S Finlay International Journal of Forecasting 28 (1), 224-238, 2012 | 266 | 2012 |
| Feature selection for time series prediction–A combined filter and wrapper approach for neural networks SF Crone, N Kourentzes Neurocomputing 73 (10-12), 1923-1936, 2010 | 256 | 2010 |
| Genetic algorithms for support vector machine model selection S Lessmann, R Stahlbock, SF Crone The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006 | 180 | 2006 |
| Multivariate k-nearest neighbour regression for time series data—A novel algorithm for forecasting UK electricity demand FH Al-Qahtani, SF Crone The 2013 international joint conference on neural networks (IJCNN), 1-8, 2013 | 156 | 2013 |
| Automatic time series analysis for electric load forecasting via support vector regression S Maldonado, A Gonzalez, S Crone Applied Soft Computing 83, 105616, 2019 | 115 | 2019 |
| A comparison of AdaBoost algorithms for time series forecast combination DK Barrow, SF Crone International Journal of Forecasting 32 (4), 1103-1119, 2016 | 87 | 2016 |
| Crogging (cross-validation aggregation) for forecasting—A novel algorithm of neural network ensembles on time series subsamples DK Barrow, SF Crone The 2013 international joint conference on neural networks (IJCNN), 1-8, 2013 | 85 | 2013 |
| Cross-validation aggregation for combining autoregressive neural network forecasts DK Barrow, SF Crone International Journal of Forecasting 32 (4), 1120-1137, 2016 | 81 | 2016 |
| Neuronale Netze zur Prognose und Disposition im Handel S Crone Springer-Verlag, 2010 | 73 | 2010 |
| Optimizing Hyperparameters of Support Vector Machines by Genetic Algorithms. S Lessmann, R Stahlbock, SF Crone IC-AI 74, 82, 2005 | 73 | 2005 |
| Stepwise selection of artificial neural network models for time series prediction SF Crone Journal of Intelligent Systems 14 (2-3), 99-122, 2005 | 68 | 2005 |
| Meta-learning with neural networks and landmarking for forecasting model selection an empirical evaluation of different feature sets applied to industry data M Kück, SF Crone, M Freitag 2016 international joint conference on neural networks (IJCNN), 1499-1506, 2016 | 60 | 2016 |
| The Impact of Preprocessing on Support Vector Regression and Neural Networks in Time Series Prediction. SF Crone, J Guajardo, R Weber DMIN, 37-44, 2006 | 60 | 2006 |
| Training artificial neural networks for time series prediction using asymmetric cost functions SF Crone Proceedings of the 9th International Conference on Neural Information …, 2002 | 59 | 2002 |
| Supply chain forecasting: Best practices & benchmarking study M Weller, S Crone Lancaster Centre For Forecasting 1 (1), 1-43, 2012 | 58 | 2012 |
Stefan LessmannProfessor of Information Systems, Humboldt-University of BerlinDirección de correo verificada de hu-berlin.de
